Recent years have witnessed significant progress in the field of neural surface
reconstruction. While extensive focus was put on volumetric and implicit approaches, a …

This paper proposes a new marker-less approach to capturing human performances from
multi-view video. Our algorithm can jointly reconstruct spatio-temporally coherent geometry …

We develop a learning framework for building deformable templates, which play a
fundamental role in many image analysis and computational anatomy tasks. Conventional …

We describe how to learn a compact and efficient model of the surface deformation of
human hands. The model is built from a set of noisy depth images of a diverse set of …

This paper presents a method for acquiring dense nonrigid shape and deformation from a
single monocular depth sensor. We focus on modeling the human hand, and assume that a …

Abstract After an earthquake, Terrestrial Laser Scanning (TLS) can capture point clouds of
the damaged state of building facades rapidly, remotely and accurately. A long-term …

We present a novel algorithm to jointly capture the motion and the dynamic shape of
humans from multiple video streams without using optical markers. Instead of relying on …

We present a dense 3D correspondence finding method that enables spatio-temporally
coherent reconstruction of surface animations from multi-view video data. Given as input a …

The reconstruction of an object's shape or surface from a set of 3D points plays an important
role in medical image analysis, eg in anatomy reconstruction from tomographic …

In this paper, we describe a novel approach for the reconstruction of animated meshes from
a series of time‐deforming point clouds. Given a set of unordered point clouds that have …